PPNP and APPNP

TensorFlow and PyTorch implementations of the model proposed in the paper:

Predict then Propagate: Graph Neural Networks meet Personalized PageRank
by Johannes Klicpera, Aleksandar Bojchevski, Stephan Günnemann
Published at ICLR 2019.

Run the code

The easiest way to get started is by looking at the notebook

simple_example_tensorflow.ipynb

simple_example_pytorch.ipynb

reproduce_results.ipynb

Requirements

The repository uses these packages:

numpy
scipy
tensorflow>=1.6,<2.0
pytorch>=1.5

You can install all requirements via

pip install -r requirements.txt

networkx_to_sparsegraph

Installation

To install the package, run

python setup.py install

Datasets

In the

data

networkx_to_sparsegraph

ppnp.data.io

The Cora-ML graph was extracted by Aleksandar Bojchevski, and Stephan Günnemann. "Deep gaussian embedding of attributed graphs: Unsupervised inductive learning via ranking." ICLR 2018,
while the raw data was originally published by Andrew Kachites McCallum, Kamal Nigam, Jason Rennie, and Kristie Seymore. "Automating the construction of internet portals with machine learning." Information Retrieval, 3(2):127–163, 2000.

The Citeseer graph was originally published by Prithviraj Sen, Galileo Namata, Mustafa Bilgic, Lise Getoor, Brian Gallagher, and Tina Eliassi-Rad. "Collective Classification in Network Data." AI Magazine, 29(3):93–106, 2008.

The PubMed graph was originally published by Galileo Namata, Ben London, Lise Getoor, and Bert Huang. "Query-driven Active Surveying for Collective Classification". International Workshop on Mining and Learning with Graphs (MLG) 2012.

The Microsoft Academic graph was originally published by Oleksandr Shchur, Maximilian Mumme, Aleksandar Bojchevski, Stephan Günnemann. "Pitfalls of Graph Neural Network Evaluation". Relational Representation Learning Workshop (R2L), NeurIPS 2018.

Contact

Please contact [email protected] in case you have any questions.

Cite

Please cite our paper if you use the model or this code in your own work:

@inproceedings{klicpera_predict_2019,
    title = {Predict then Propagate: Graph Neural Networks meet Personalized PageRank},
    author = {Klicpera, Johannes and Bojchevski, Aleksandar and G{\"u}nnemann, Stephan},
    booktitle={International Conference on Learning Representations (ICLR)},
    year = {2019}
}